Telomere attrition becomes an instrument for clonal selection in aging hematopoiesis and leukemogenesis.

The mechanisms through which mutations in splicing factor genes drive clonal hematopoiesis (CH) and myeloid malignancies, and their close association with advanced age, remain poorly understood. Here we show that telomere maintenance plays an important role in this phenomenon. First, by studying 454,098 UK Biobank participants, we find that, unlike most CH subtypes, splicing-factor-mutant CH is more common in those with shorter genetically predicted telomeres, as is CH with mutations in PPM1D and the TERT gene promoter.

Untargeted lipidomic deep-profiling of human plasma via high-performance aza-Prilezhaev aziridination-LC-MS: Unraveling CC isomeric signatures of Charcot-Marie-Tooth disease.

Background: Perturbed lipid metabolism in cellular environment plays an essential role in the progression of peripheral neuropathy, such as Charcot-Marie-Tooth disease type 1A (CMT1A). Current deep-profiling of lipidome still has certain limitations for high-throughput analysis of clinical samples, such as low sensitivity, extensive requirement of instrument modification, technician-dependent pretreatment and lack of method-adapted data-processing software.

Results: Herein, a new generation aza-Prilezhaev aziridination (APA) reagent has been designed for coupling with high-resolution liquid chromatography mass spectrometry (LC-MS) to conduct comprehensive untargeted deep lipidomics of CMT1A disease.

Proposed Nomenclature for Landmarks in Anterior-Segment OCT: The APOSTEL-AS Panel Consensus.

Importance: Anterior-segment optical coherence tomography (AS-OCT) has broad clinical and research utility. The utility of quantitative data derived from AS-OCT is, however, dependent on the quality and consistency of the cumulative evidence base.

Objective: To develop consensus-based nomenclature that supports standardized reporting of AS-OCT image acquisition and analyses as a foundation to improve research reproducibility.

Reporting guideline for chatbot health advice studies: The CHART statement.

The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice, referred to as Chatbot Health Advice (CHA) studies. CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting and methodology in CHA studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary modified asynchronous Delphi consensus process of 531 stakeholders, three synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist.

Reporting Guideline for Chatbot Health Advice Studies: The CHART Statement.

Importance: The rise in chatbot health advice (CHA) studies is accompanied by heterogeneity in reporting standards, impacting their interpretability.

Objective: To provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice.

Design, Setting, And Participants: CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and methodology in CHA studies.

Reporting guideline for Chatbot Health Advice studies: the CHART statement.

Background: The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice, referred to as Chatbot Health Advice (CHA) studies.

Methods: CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and methodology in CHA studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary modified asynchronous Delphi consensus process of 531 stakeholders, three synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist.

Driving Safety among Adolescents with Health Conditions: An Integrative Review.

Introduction: Obtaining a driver's license enhances independence and quality of life but can be challenging for adolescents with health conditions. Health conditions may impact driving behavior and not always require driving restrictions. Strategies that promote safe independent driving for adolescents with various health conditions are not well described.

Sex differences in Acinetobacter baumannii infections: A comprehensive analysis of antibiotic resistance patterns in Hebei Province, China.

Background: To investigate the clinical distribution and antimicrobial resistance patterns of Acinetobacter baumannii in Hebei Province, with a focus on sex-based differences.

Methods: Surveillance data from 45 hospitals across Hebei Province were retrospectively analyzed from January 2020 to December 2022. Isolates were stratified by patient sex, age group, and specimen type.

Association Between Smartphone Attachment and Mental Health in Adolescents.

Background: The surge in adolescent smartphone use has coincided with the rise in the adolescent mental health crisis, raising public health concerns. Moving beyond the traditional focus on screen time, this study examined the association between smartphone attachment and mental health among adolescents.

Methods: Data were analyzed from 137 community-dwelling adolescents (aged 16.

Crop Statistic to Annual Map: Tracking spatiotemporal dynamics of crop-specific areas through machine learning and statistics disaggregating.

Mapping spatiotemporal dynamics of crop-specific areas is of great significance in addressing challenges faced by agricultural systems. But comparable multi-phase crop maps in year series have not yet been developed in most regions of the global. In this study, we developed a framework for updating annual crop-specific area maps at 10 km resolution based on crop statistics disaggregating, multi-source data integrating and machine learning.

Solvent Exchange Strengthening Interpenetrating Dual-Network Organohydrogels with Anti-icing Durability and Friction Resistance.

Developing mechanically robust hydrogels with low ice adhesion and anti-icing durability in low-temperature environments (≤ -20 °C) remains a persistent challenge. In this study, a dual-network organohydrogel (PAD) was synthesized through a facile one-pot copolymerization of acrylamide (AM), and [2-(Methacryloyloxy)-ethyl]-trimethylammonium chloride (DML) dissolved in poly-(vinyl alcohol) (PVA) aqueous solution, followed by solvent exchange in a mixed solvent of dl-1,2-Isopropylideneglycerol-(ACM) and water (HO). This unique solvent exchange enhances chain entanglement within the interpenetrating dual networks and establishes robust hydrogen bonding interactions.

A decomposition of Fisher's information to inform sample size for developing or updating fair and precise clinical prediction models for individual risk-part 1: binary outcomes.

Background: When using a dataset to develop or update a clinical prediction model, small sample sizes increase concerns of overfitting, instability, poor predictive performance and a lack of fairness. For models estimating the risk of a binary outcome, previous research has outlined sample size calculations that target low overfitting and a precise overall risk estimate. However, more guidance is needed for targeting precise and fair individual-level risk estimates.

Cancer pain and quality of life structural equation model based on the biopsychosocial model.

Objective: This study employed a biopsychosocial framework to develop structural equation models(SEM)quantifying the multidimensional impact of pain on quality of life in cancer patients, aiming to provide scientific evidence and novel clinical perspectives for evidence-based pain management strategies.

Methods: This cross-sectional study recruited participants experiencing chronic cancer-related pain using convenience sampling from a tertiary cancer hospital in Shandong Province, China, between January and February 2024. Data collection involved face-to-face administration of the Brief Pain Inventory-Short Form and the Quality of Life Questionnaire-Function 17.

Posttranscriptional depletion of ribosome biogenesis factors engenders therapeutic vulnerabilities in NPM1-mutant AML.

NPM1 is a multifunctional phosphoprotein with key roles in ribosome biogenesis among its many functions. NPM1 gene mutations drive 30% of acute myeloid leukemia (AML) cases. The mutations disrupt a nucleolar localization signal and create a novel nuclear export signal, leading to cytoplasmic displacement of the protein (NPM1c).

A scoping review and evidence gap analysis of clinical AI fairness.

The ethical integration of artificial intelligence (AI) in healthcare necessitates addressing fairness. AI fairness involves mitigating biases in AI and leveraging AI to promote equity. Despite advancements, significant disconnects persist between technical solutions and clinical applications.

Nerve Diameter and DTI Parameters Maybe Potential Markers for Clinical Trial in Patients With Charcot-Marie-Tooth Disease Type 1A.

Background: Charcot-Marie-Tooth disease type 1A (CMT1A) is the most common form of CMT, varying from asymptomatic to severe. The aim of this study was to investigate whether the diffusion tensor imaging (DTI) parameters and diameter of the proximal nerves, as measured by magnetic resonance neurography, can be used as a potential marker to reflect the progression.

Methods: This was a prospective study including 45 consecutive patients with CMT1A, divided into three subgroups by foot dorsiflexion muscle strength: mild cases (Group 1), moderate cases (Group 2), and severe cases (Group 3).

Studies on nanoprotein vaccine alleviating symptoms of mice allergic to rFel d 1.

Introduction: Globally, cat allergens are a common cause of allergic rhinitis and asthma. Fel d 1 is the primary allergen among cat allergens and can induce a broad range of allergies through airborne transmission.

Methods: In our study, we constructed layered double hydroxide (LDH) nanoparticles loaded with PADRE-rFel d 1, aiming to address allergies triggered by Fel d 1.

Target product profiles for digital health technologies including those with artificial intelligence: a systematic review.

Digital health technologies (DHTs), including those incorporating artificial intelligence (AI), have the potential to improve healthcare access, efficiency, and quality, reducing gaps between healthcare capacity and demand. Despite prioritisation in health policy, the adoption of DHTs remains limited, especially for AI, in part due to complex system requirements. Target product profiles (TPPs) are documents outlining the characteristics necessary for medical technologies to be utilised in practice and offer a way to align DHTs' research and development with health systems' needs.

Importance of sample size on the quality and utility of AI-based prediction models for healthcare.

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the determination of appropriate sample sizes for studies developing AI-based prediction models for individual diagnosis or prognosis. Specifically, the number of participants and outcome events required in datasets for model training and evaluation remains inadequately addressed.

A scoping review of artificial intelligence as a medical device for ophthalmic image analysis in Europe, Australia and America.

This scoping review aims to identify regulator-approved ophthalmic image analysis artificial intelligence as a medical device (AIaMD) in three jurisdictions, examine their characteristics and regulatory approvals, and evaluate the available evidence underpinning them, as a step towards identifying best practice and areas for improvement. 36 AIaMDs from 28 manufacturers were identified - 97% (35/36) approved in the EU, 22% (8/36) in Australia, and 8% (3/36) in the USA. Most targeted diabetic retinopathy detection.